Current methods for detecting issues and analyzing disruptions within telecommunications networks are often reactive, such that diagnostic and corrective action is not initiated until after problems have been reported. This leads to a poor experience for network users as they must deal with interrupted services and face lengthy issue-resolution times. The identification of deviations or anomalies from normal or expected patterns of communication transactions can be very useful for proactively identifying network issues before they have a significant impact on users, and enabling the diagnostic and corrective action to be initiated promptly. Furthermore, the ability to analyse communication transactions in this way provides a valuable means for accelerating both the diagnosis and resolution of such issues.
In addition, such an analysis of communication transactions can also be used to identify system design issues in order to optimise network configuration and utilisation, identify fraudulent behaviour etc. Moreover, such an analysis can also be used as a means for identifying and even interpreting significant events (e.g. weather, social, political and economic events). For example, it is possible to use the analysis of deviations in the expected patterns of mobile telecommunications such as calls and text messages to identify events such as crisis situations and the early signs of epidemics.
With the rapid advancement and wide-spread uptake of communication technologies, there are now vast numbers of communication transactions taking place daily. For example, worldwide there are more than 200 billion emails, 4 billion text messages and 90 million tweets sent every day. Consequently, one of the main problems faced when attempting to implement an analysis of communication transaction data is the massive amounts of data involved, and the incredible rate at which new data is created. In particular, communication transaction data is usually so substantial, dynamic and varied that it is extremely difficult to carry out a meaningful and conclusive analysis in a short space of time.
In view of the above an analysis system is desirable which assists with the efficient identification of deviations or anomalies in normal or expected patterns of transactions, entries or events, and the interpretation or diagnosis of the cause of these deviations or anomalies.